Generated Code
The following is python code generated by the CellML API from this CellML file. (Back to language selection)
The raw code is available.
# Size of variable arrays:
sizeAlgebraic = 0
sizeStates = 2
sizeConstants = 16
from math import *
from numpy import *
def createLegends():
legend_states = [""] * sizeStates
legend_rates = [""] * sizeStates
legend_algebraic = [""] * sizeAlgebraic
legend_voi = ""
legend_constants = [""] * sizeConstants
legend_voi = "time in component environment (minute)"
legend_states[0] = "Pha in component Pha (millimolar)"
legend_constants[0] = "V_1 in component Pha (per_minute)"
legend_constants[1] = "K_1 in component Pha (dimensionless)"
legend_constants[2] = "K_2 in component Pha (dimensionless)"
legend_constants[3] = "V_M2 in component Pha (per_minute)"
legend_constants[4] = "alpha in component Pha (dimensionless)"
legend_constants[5] = "GLC in component Pha (millimolar)"
legend_constants[6] = "K_a1 in component Pha (millimolar)"
legend_constants[7] = "K_a2 in component Pha (millimolar)"
legend_states[1] = "GSa in component GSa (millimolar)"
legend_constants[8] = "V_M3 in component GSa (per_minute)"
legend_constants[9] = "beta in component GSa (dimensionless)"
legend_constants[10] = "G6P in component GSa (millimolar)"
legend_constants[11] = "K_a3 in component GSa (millimolar)"
legend_constants[12] = "K_3 in component GSa (dimensionless)"
legend_constants[13] = "K_4 in component GSa (dimensionless)"
legend_constants[14] = "K_a4 in component GSa (millimolar)"
legend_constants[15] = "V_4 in component GSa (per_minute)"
legend_rates[0] = "d/dt Pha in component Pha (millimolar)"
legend_rates[1] = "d/dt GSa in component GSa (millimolar)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
states[0] = 0.845
constants[0] = 1.25
constants[1] = 0.1
constants[2] = 0.2
constants[3] = 0.22
constants[4] = 9
constants[5] = 32.5
constants[6] = 10
constants[7] = 10
states[1] = 0.02
constants[8] = 0.05
constants[9] = 9
constants[10] = 0.4
constants[11] = 0.5
constants[12] = 0.4
constants[13] = 0.4
constants[14] = 0.5
constants[15] = 0.2
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
rates[0] = (constants[0]*(1.00000-states[0]))/((constants[1]+1.00000)-states[0])-(constants[3]*states[0]*(1.00000+(constants[4]*constants[5])/(constants[6]+constants[5])))/(constants[2]/(1.00000+constants[5]/constants[7])+states[0])
rates[1] = (constants[8]*(1.00000+(constants[9]*constants[10])/(constants[11]+constants[10]))*(constants[1]/(constants[1]+states[0]))*(1.00000-states[1]))/((constants[12]/(1.00000+constants[10]/constants[14])+1.00000)-states[1])-(constants[15]*states[1])/(constants[13]+states[1]*1.00000)
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
return algebraic
def solve_model():
"""Solve model with ODE solver"""
from scipy.integrate import ode
# Initialise constants and state variables
(init_states, constants) = initConsts()
# Set timespan to solve over
voi = linspace(0, 10, 500)
# Construct ODE object to solve
r = ode(computeRates)
r.set_integrator('vode', method='bdf', atol=1e-06, rtol=1e-06, max_step=1)
r.set_initial_value(init_states, voi[0])
r.set_f_params(constants)
# Solve model
states = array([[0.0] * len(voi)] * sizeStates)
states[:,0] = init_states
for (i,t) in enumerate(voi[1:]):
if r.successful():
r.integrate(t)
states[:,i+1] = r.y
else:
break
# Compute algebraic variables
algebraic = computeAlgebraic(constants, states, voi)
return (voi, states, algebraic)
def plot_model(voi, states, algebraic):
"""Plot variables against variable of integration"""
import pylab
(legend_states, legend_algebraic, legend_voi, legend_constants) = createLegends()
pylab.figure(1)
pylab.plot(voi,vstack((states,algebraic)).T)
pylab.xlabel(legend_voi)
pylab.legend(legend_states + legend_algebraic, loc='best')
pylab.show()
if __name__ == "__main__":
(voi, states, algebraic) = solve_model()
plot_model(voi, states, algebraic)
